CN109348404A - A kind of method that individual trip path locus extracts under big data environment - Google Patents
A kind of method that individual trip path locus extracts under big data environment Download PDFInfo
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- CN109348404A CN109348404A CN201811180884.8A CN201811180884A CN109348404A CN 109348404 A CN109348404 A CN 109348404A CN 201811180884 A CN201811180884 A CN 201811180884A CN 109348404 A CN109348404 A CN 109348404A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
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Abstract
The present invention relates to a kind of methods that individual trip path locus extracts under big data environment.The invention has the advantages that leveraging fully on the communication big data resource between the mobile terminal and sensor that existing user holds, utilize the lasting encryption position information of magnanimity anonymity mobile terminal existing in communication network, it can low cost, automation, the trip Time-space serials for easily obtaining a large amount of individuals within the scope of specified time, using the method for spatial analysis and spatial operation, according to the communications records between individual and fixed sensor, the network path of most probable of the individual between communication node is excavated, it is final to arrange the motion track for obtaining individual between O-D point.
Description
Technical field
The present invention relates to a kind of gone on a journey based on magnanimity individual to record spatial position and time individual in data, passes through calculating
The movement speed of individual is extracted possible space motion track of the individual between trip record on classification road network, is used
The method of probability distribution, the method for excavating movement track of the individual on classification space road network.
Background technique
In recent years, as explosive growth is presented in the development of information technology, data information amount, data source is more and more,
Data volume is also more and more huger.Wherein, have become big number by the data that the information sensors such as mobile phone, WIFI, Internet of Things record
According to data source most important in analysis, more complete individual trip is recorded as big data, especially traffic big data point
Analysis provides good data and supports.It takes the mobile phone as an example, until 2015, mobile phone user reaches 13.06 hundred million, accounts for total population
96% or more, the signal message that mobile phone terminal equipment persistently generates forms the volume of data collection of record user's trip, to hand over
The analysis of pass-out row provides important data source.
However, being hand-held mobile terminal and fixation by the data basis of the mobile communication big data of representative of mobile phone big data
Communications records between sensor, this basic data for allowing for mobile communication big data be it is discrete rather than continuous, it is right
Trip track of the individual in spatial network is identified and extracted from the communication record data of individual and fixed sensor bring difficulty.
On the other hand, the general and non-rice habitats of the location of fixed sensor, this allows for road network track of going on a journey to individual space
Data basis of extraction itself is not on network connectivity.
Summary of the invention
The object of the present invention is to provide certain algorithms to process individual trip log data set, based on this
Trip track of the individual on the road network of space is excavated, to be conducive to precisely identify individual trip track, is effectively judged
The load capacity of road network at times.
In order to achieve the above object, the technical solution of the present invention is to provide individual trip roads under a kind of big data environment
The method of trajectory extraction, which comprises the following steps:
Step 1, the anonymity obtained within the scope of certain time from sensor operator encrypt mobile terminal sensing data,
Null record when being gone on a journey for each user building by the preliminary individual that individual and fixed sensor communications records are constituted, senses fixed
The geographical attribute of device assigns each communication node in preliminary individual trip space-time trajectory, constructs individual trip space-time data with this
Collection；
Step 2 arranges individual trip space-time data collection in chronological order, is remembered with the communication between individual and fixed sensor
Record is node, constructs individual trip Time-space serial, the trip O-D point in individual trip Time-space serial is identified, when individual is gone on a journey
Empty sequence is cut according to O-D point, is divided into several sections O-D, and every section is numbered, and constitutes the individual trip section O-D number
According to collection；
Step 3, according to the individual trip section O-D data set, calculate individual in trip section two-by-two between node away from
From, spend time and average speed, according to the speed between node two-by-two in individual trip section, by constructing network model, with
The real road network of communication lines is geographical substrate, calculates individual possible individual trip route, including following step between the two nodes
It is rapid:
Step 3.1, arrange individual where city road traffic net, by every roads classification in road traffic net, according to
Average movement speed of the every kind of trip mode on every road in each period is obtained according to available data；
Step 3.2, by all communication nodes in the individual trip section O-D data set in individual every section O-D according to
Its spatial position projects in road traffic net, searches the road traffic net junction node nearest apart from each communication node, fixed
Justice is R point, using R point as the S-T point between communication node two-by-two, the shortest distance of calculating communication node to respective S-T point；
Step 3.3 extracts the shortest distance and its path between communication node two-by-two, calculate that shortest path spends when
Between；
Step 3.4 is cut apart with a knife or scissors the shortest path between communication node two-by-two by section, and the direction in space for calculating shortest path is multiple
Miscellaneous degree SDF, the direction in space complexity SDF, which are used, asks weighting standard difference to obtain the moving direction of pavement branch sections；
If the traveling time of step 3.5, individual between communication node two-by-two is less than or equal to the time that shortest path is spent,
Shortest path is practical mobile section of the individual between communication node two-by-two；Otherwise, spatial operation model is constructed, using solution side
The method of journey group, using direction in space complexity SDF as objective function, solves individual in space using traveling time as constraint condition
In motion track, the motion track is as practical mobile section of the individual between communication node two-by-two；
Step 3.6 will solve obtained practical mobile section both ends plus the shortest distance of the communication node to S-T point, structure
At the most probable individual trip route between communication node two-by-two；
Step 4, to the most probable individual trip route that all communication nodes two-by-two are calculated carry out arrange and space melt
It closes, it is final to obtain specific individual trip track.
Preferably, in the step 3.4, if individual k-th of section between i-th of communication node and j-th of communication node
Moving direction beAnd have N section, i.e. k=1 between i-th of communication node and j-th of communication node, 2 ..., N, then
The average value of individual section moving directions all between i-th of communication node and j-th of communication node is calculated firstWithIt is 0 degree, the direction that individual moves on N section is adjusted in [- 180,180] section, then k-th
The moving direction in section is adjusted toThen between i-th of communication node and j-th of communication node between direction in space complexity can
It indicates are as follows:
In formula,Indicate the length in k-th of section.
Preferably, it is assumed that there is L side in road traffic net, there is M junction node, starting point is node B, and terminal is node D,
Then the equation group in the step 3 indicates are as follows:
s.t.
In formula,Indicate the SDF value of shortest path；
SDF is the SDF value of solution path；
lm,n(0-1) Boolean variable, indicate m-th of junction node to the section of n-th of junction node by with
In solution path, if lm,n=1 indicates that the section of m-th of junction node to n-th of junction node is used for what solution obtained
In path, otherwise lm,n=0；
INmIt indicates in solving obtained path, number of the individual from m-th of junction node；OUTmExpression is solving
In obtained path, individual reaches the number of m-th of junction node；According to theorem on flows in network, if m-th of junction node is individual
Starting point, then INm-OUTm=-1, if m-th of junction node is the terminal of individual, INm-OUTm=1, remaining intermediate node
INm-OUTm=0；
TIMES,TIndicate the time difference between communication node；
vm,n,t,pIt indicates in time range t, pth kind trip mode is in m-th of junction node to the road of n-th of junction node
The average movement speed of section；
It indicates using pth kind trip mode in time range t, along solving obtained path from B
Point arrives D point the time it takes, rm,nIndicate m-th of junction node to n-th of junction node road section length.
Preferably, the step 4 includes:
Step 4.1 pieces together the most probable path between communication node two-by-two, constitutes the preliminary complete road O-D
Diameter；
Step 4.2, in addition to O point and D point, remove in the path O-D from communication node to away from nearest traffic intersection
Distance, it is online that the path O-D is mapped completely to road traffic；
Step 4.3 traverses forward backward simultaneously from each R point, if there are duplicate paths near R point, deletes
Section is repeated, until there is no continuous repetition section, i.e., individual reaches R point by section k to i to j, then passes through road
Section j to i's to l leaves R point, then deletes section i to j and j to i, and individual is recorded directly from k to i to l and merges point i；
Step 4.4, each merging point i of traversal traverse forward backward again from point is merged, if merging the nth road backward point i
The direction of section a to b subtracts 180 degree, and the difference of the angular separation of nth section x to y is less than threshold value C, and this two sections forward
Between be connection, then the section between this two sections is all deleted, individual is directly from a to y；
Step 4.5 after deleting redundancy section, rearranges trip route of the individual between O-D point, completes individual O-
The trajectory extraction of the space road traffic net of D trip.
It the present invention is based on mobile terminal big data, is handled and is screened, by the held mobile terminal of individual and fixed sensing
Communications records between device construct the space-time data collection of individual trip；By individual trip O-D point identification, when individual is gone on a journey
Empty sequence is split as single O-D trip record；By calculating time and speed of the individual on the path O-D between communication node
Degree excavates the most probable path between communication node in the Traffic Net of space；It is obtaining between communication node two-by-two most
The path can further be arranged on the basis of several paths, it is final to obtain individual handing between O-D point in space road
Lead to online motion track.
The invention has the advantages that the communication leveraged fully between the mobile terminal and sensor that existing user holds counts greatly
It can be inexpensive, automatic using having the lasting encryption position information of magnanimity anonymity mobile terminal in communication network according to resource
Change, easily obtain a large amount of individual trip Time-space serials within the scope of specified time, using the side of spatial analysis and spatial operation
Method excavates the network of most probable of the individual between communication node according to the communications records between individual and fixed sensor
Path, it is final to arrange the motion track for obtaining individual between O-D point.
Detailed description of the invention
Fig. 1 is overview flow chart of the invention.
Specific embodiment
Present invention will be further explained below with reference to specific examples.It should be understood that these embodiments are merely to illustrate the present invention
Rather than it limits the scope of the invention.In addition, it should also be understood that, after reading the content taught by the present invention, those skilled in the art
Member can make various changes or modifications the present invention, and such equivalent forms equally fall within the application the appended claims and limited
Range.
In conjunction with Fig. 1, the method that individual trip path locus extracts under a kind of big data environment provided by the invention, including with
Lower step:
Step 1, the anonymity obtained within the scope of certain time from sensor operator encrypt mobile terminal sensing data,
Null record when being gone on a journey for each user building by the preliminary individual that individual and fixed sensor communications records are constituted, passes fixed
The geographical attribute of sensor assigns each communication node in individual trip space-time trajectory, constructs individual trip space-time data with this
Collection；
Anonymity encryption mobile terminal sensing data is operator from mobile communications network, fixed broadband network, wireless
WIFI and location-based service correlation APP etc. are obtained in real time and the encrypted location for the encrypted anonymous mobile phone user's time series that desensitizes
Information, content includes: EPID, TYPE, TIME, REGIONCODE, SENSORID, referring to application No. is 201610273693.0
Chinese patent.It is specifically described as follows:
EPID (anonymous One-Way Encryption whole world unique mobile terminal identification code, EncryPtion international
Mobile subscriber IDentity), it is that unidirectional irreversible encryption is carried out to each mobile terminal user, to uniquely mark
Know each mobile terminal user, and do not expose Subscriber Number privacy information, it is desirable that each encrypted EPID of mobile terminal user
Uniqueness is kept, i.e. the EPID of any time each mobile phone user is remained unchanged and do not repeated with other mobile phone users.
TYPE is communication operation type involved in current record, e.g., online, call, calling and called, transmitting-receiving short message, GPS
Positioning, the switching of sensor cell, sensor switching, switching on and shutting down etc..
TIME is that the moment occurs for communication operation involved in current record, and unit is millisecond.
REGIONCODE, SENSORID are the sensor encrypted bits confidences that communication operation involved in current record occurs
Breath.The number of REGIONCODE, SENSORID sensor, wherein great Qu, SENSORID locating for REGIONCODE representative sensor
It is the number of specific sensor.
Step 1.1, system read from sensor operator and obtain anonymous encryption mobile terminal sensing data, theoretically hide
Name encryption mobile terminal sensing data all should be continuous in the time and space, comprising: user's unique number EPID, lead to
Believe that great Qu REGIONCODE locating for moment TIME, sensor, sensing implement body number occur for type of action TYPE, communication operation
SENSORID；Wherein, great Qu REGIONCODE locating for sensor and sensing implement body number SENSORID constitute sensor volume
Number, detailed data format and manner of decryption are shown in patent (201610386914.5)；
Step 1.3, according to Customs Assigned Number EPID, inquire its at the appointed time log all in section, construct user
Trip data；
In this example, the real-time signaling record data of the user and sensor that extract are shown in Table 1:
Table 1: new received real-time signaling records data after decryption
Step 2 arranges individual trip record in chronological order, is section with the communications records between individual and fixed sensor
Point constructs individual trip Time-space serial, identifies trip O-D point therein, and individual trip Time-space serial is cut apart with a knife or scissors according to O-D point,
Constitute individual trip section data set.Step 2 the following steps are included:
Step 2.1 will communicate during individual trip with fixed sensor and be formed by space-time data collection according to time sequence
Column sequence constructs individual trip Time-space serial data, according to the time and space information of space-time data collection nodes records, calculate node
Between Euclidean distance, individual average movement speed among the nodes is calculated with this；
In this example, the time difference between communication node and distance are shown in Table 2:
Table 2: time difference and distance between communication node
Step 2.2, using the method for space interpolation and space clustering, according to average movement speed of the individual between node,
It excavates it and stops place for a long time during trip, as the O-D point of individual trip, judge the O-D of individual trip
Section, the method detailed of this part are shown in patent (201710843841.2)；
In this example, the section an O-D sample in individual trip Time-space serial is shown in Table 3:
The section O-D sample in 3 individual trip Time-space serial of table
| RECORDID | EPID | TYPE | TIMESTAMP | REGIONCODE | SENSORID | X | Y |
| R1074 | E1 | T1 | 2017-11-22 07:35:06 | 9622 | 3415 | 4774.443 | 5863.045 |
| R1075 | E1 | T1 | 2017-11-22 08:04:45 | 9622 | 6543 | 5568.195 | 6048.254 |
| R1076 | E1 | T1 | 2017-11-22 08:34:22 | 9622 | 3212 | 6176.738 | 6286.379 |
| R1077 | E1 | T2 | 2017-11-22 08:44:36 | 9622 | 4632 | 6944.031 | 6603.88 |
| R1078 | E1 | T2 | 2017-11-22 09:01:24 | 9622 | 6343 | 7790.699 | 6550.963 |
| R1079 | E1 | T3 | 2017-11-22 09:13:41 | 9622 | 1242 | 8478.617 | 6259.921 |
| R1080 | E1 | T3 | 2017-11-22 09:26:59 | 9622 | 1253 | 8769.66 | 5704.295 |
| R1081 | E1 | T3 | 2017-11-22 09:51:41 | 9622 | 3223 | 9166.535 | 5280.96 |
| R1082 | E1 | T2 | 2017-11-22 10:12:38 | 9622 | 3421 | 9669.245 | 4989.918 |
| R1083 | E1 | T1 | 2017-11-22 10:33:27 | 9622 | 7645 | 9023.341 | 4704.424 |
Step 2.3 carries out and sentences to the trip vehicles of individual according to movement speed of the individual between communication node
It is disconnected, judge its trip mode for walking, drive or ride a bicycle；
In this example, individual trip speed average between O-D node is 700 ms/min, and reckoning trip mode is machine
Motor-car trip；
Step 2.4 cuts individual trip Time-space serial data according to O-D point, is divided into several sections O-D, will be every
Section number (in this example, the number of the section O-D shown in table 3 is R1), constitutes the individual section O-D data set.
Step 3, calculate individual in trip section two-by-two the distance between node, spend time and average speed, according to
The speed between node by constructing network model is geographical substrate, meter with the real road network of communication lines two-by-two in individual trip section
Calculate individual path possible between the two nodes.Step 3 the following steps are included:
Step 3.1, the road traffic net for arranging individual place city obtain every roads classification according to available data
Average movement speed of the every kind of trip mode on every road in each period；
Average movement speed mode of transportation example of the different trip modes of table 4 on different brackets road
| Mode of transportation | Category of roads | Average speed |
| … | … | … |
| Walking | Ordinary Rd | 85 ms/min |
| It cycles | Ordinary Rd | 260 ms/min |
| Self-driving | Viaduct | 1200 ms/min |
| Motor vehicle | Ordinary Rd | 730 ms/min |
| Subway | Subway | 400 ms/min |
| Motor vehicle | Through street | 900 ms/min |
| … | … | … |
All communication nodes in individual every section O-D are projected road traffic net according to its spatial position by step 3.2
In, search the road traffic net junction node nearest apart from each communication node, referred to as R point, using the node as communicating two-by-two
S-T point between node, the shortest distance of calculating communication node to respective S-T point；In this example, each in the R1 of the section O-D
The R point of node is shown in Table 4:
In 4 section O-D R1 of table the point position R of each node at a distance from node
| RECORDID | EPID | TYPE | TIMESTAMP | X | Y | RX | RY | Distance |
| R1074 | E1 | T1 | 2017-11-22 07:35:06 | 4774.443 | 5863.045 | 4772.443 | 5846.045 | 17.117 |
| R1075 | E1 | T1 | 2017-11-22 08:04:45 | 5568.195 | 6048.254 | 5560.195 | 6043.254 | 9.434 |
| R1076 | E1 | T1 | 2017-11-22 08:34:22 | 6176.738 | 6286.379 | 6192.738 | 6282.379 | 16.492 |
| R1077 | E1 | T2 | 2017-11-22 08:44:36 | 6944.031 | 6603.88 | 6925.031 | 6593.880 | 21.471 |
| R1078 | E1 | T2 | 2017-11-22 09:01:24 | 7790.699 | 6550.963 | 7795.699 | 6537.963 | 13.928 |
| R1079 | E1 | T3 | 2017-11-22 09:13:41 | 8478.617 | 6259.921 | 8489.617 | 6271.921 | 16.279 |
| R1080 | E1 | T3 | 2017-11-22 09:26:59 | 8769.66 | 5704.295 | 8780.660 | 5700.295 | 11.705 |
| R1081 | E1 | T3 | 2017-11-22 09:51:41 | 9166.535 | 5280.96 | 9179.535 | 5268.960 | 17.692 |
| R1082 | E1 | T2 | 2017-11-22 10:12:38 | 9669.245 | 4989.918 | 9673.245 | 5001.918 | 12.649 |
| R1083 | E1 | T1 | 2017-11-22 10:33:27 | 9023.341 | 4704.424 | 9017.341 | 4695.424 | 10.817 |
Step 3.3, the method using spatial analysis are extracted between communication node two-by-two using dijkstra's algorithm
The shortest distance and its path calculate the time that shortest path is spent；In this example, the shortest path between the node of the section O-D R1
Diameter and distance are shown in Table 5:
Shortest path and distance in 5 section O-D R1 of table between each node
| RECORDID | RECORDID | Distance | Rout |
| R1074 | R1075 | 1002.54 | L12-L14-L10 |
| R1075 | R1076 | 725.35 | L10-L11-L18-L19 |
| R1076 | R1077 | 963.25 | L21-L26-L31 |
| R1077 | R1078 | 1077.37 | L31-L54-L42 |
| R1078 | R1079 | 911.28 | L34-L35 |
| R1079 | R1080 | 765.23 | L36-L37 |
| R1080 | R1081 | 707.94 | L44-L45-L47-L56-L64 |
| R1081 | R1082 | 638.97 | L64-L56-L43 |
| R1082 | R1083 | 735.95 | L41-L40 |
| R1074 | R1075 | 1002.54 | L12-L14-L10 |
Step 3.4 is cut apart with a knife or scissors the shortest path between node by section, calculates the direction in space complexity SDF of shortest path；
Direction in space complexity SDF, which is used, asks weighting standard difference to obtain the moving direction of pavement branch sections: setting individual in i-th of communication node
The moving direction in k-th of section is between j-th of communication nodeAnd between i-th of communication node and j-th of communication node
There are N section, i.e. k=1,2 ..., N then calculates individual first and owns between i-th of communication node and j-th of communication node
The average value of section moving directionWithIt is 0 degree, the direction that individual moves on N section is adjusted to [-
180,180] in section, then the moving direction in k-th of section is adjusted toThen i-th of communication node and j-th of communication node
Between between direction in space complexity may be expressed as:
In formula,Indicate the length in k-th of section.
In this example, the direction complexity of shortest path is shown in Table 6 between the node of the section O-D R1:
The direction in space complexity of shortest path in table 6O-D section R1 between each node
If the traveling time of step 3.5, individual between node is less than or equal to the time that shortest path is spent, shortest path
As practical mobile section of the individual between node；Otherwise, then spatial operation model is constructed, using the method for solving equations, with
Traveling time is constraint condition, using SDF as objective function, solves the motion track of individual in space.
Assuming that there is L side in road traffic net, there is M junction node, starting point is node B, and terminal is that node D is then above-mentioned
Equation group may be expressed as:
s.t.
In formula,Indicate the SDF value of shortest path；
SDF is the SDF value of solution path；
lm,n(0-1) Boolean variable, indicate m-th of junction node to the section of n-th of junction node by with
In solution path, if lm,n=1 indicates that the section of m-th of junction node to n-th of junction node is used for what solution obtained
In path, otherwise lm,n=0；
INmIt indicates in solving obtained path, number of the individual from m-th of junction node；OUTmExpression is solving
In obtained path, individual reaches the number of m-th of junction node；According to theorem on flows in network, if m-th of junction node is individual
Starting point, then INm-OUTm=-1, if m-th of junction node is the terminal of individual, INm-OUTm=1, remaining intermediate node
INm-OUTm=0；
TIMES,TIndicate the time difference between communication node；
vm,n,t,pIt indicates in time range t, pth kind trip mode is in m-th of junction node to the road of n-th of junction node
The average movement speed of section；
It indicates using pth kind trip mode in time range t, along solving obtained path from B
Point arrives D point the time it takes, rm,nIndicate m-th of junction node to n-th of junction node road section length；
The angle in the section that the path that the calculating of SDF is also only obtained comprising solution is included
Step 3.6 will solve obtained section both ends plus communication node to the shortest distance of S-T point, asks and constitutes two
Most probable path between two communication nodes；
In this example, most probable path is shown in Table 7 between the node two-by-two of the section O-D R1:
Table 7
| RECORDID | RECORDID | Rout |
| R1074 | R1075 | L12-L13-L11-L14-L10 |
| R1075 | R1076 | L10-L6-L8-L11-L18-L17-L19 |
| R1076 | R1077 | L21-L20-L26-L29-L31 |
| R1077 | R1078 | L31-L29-L48-L54-L42 |
| R1078 | R1079 | L34-L35 |
| R1079 | R1080 | L36-L37 |
| R1080 | R1081 | L44-L45-L47-L56-L57-L58-L64 |
| R1081 | R1082 | L64-L-58-L57-L56-L43 |
| R1082 | R1083 | L41-L40-L72-L43 |
| R1074 | R1075 | L12-L14-L02-L10 |
Step 4 carries out arrangement and Space integration to the individual trip route that node two-by-two is calculated, final to obtain specifically
Individual trip track, comprising the following steps:
Step 4.1 pieces together the most probable path between communication node two-by-two, constitutes the preliminary complete road O-D
Diameter；
Step 4.2, in addition to O point and D point, remove in the path O-D from communication node to away from nearest traffic intersection
Distance, it is online that the path O-D is mapped completely to road traffic；
In this example, individual is between O-D in the track of road traffic online mobile are as follows:
L12→L13→L11→L14→L10→L10→L6→L8→L11→L18→L17→L19→L21→L20→
L26→L29→L31→L31→L29→L48→L54→L42→L34→L35→L36→L37→L44→L45→L47→
L56→L57→L58→L64→L64→L→58→L57→L56→L43→L41→L40→L72→L43→L12→L14→
L02→L10
Step 4.3 traverses forward backward simultaneously from each R point, if there are duplicate paths near R point, deletes
Section is repeated, until there is no continuous repetition section, i.e., individual reaches R point by section k to i to j, then passes through road
Section j to i's to l leaves R point, then deletes section i to j and j to i, and individual is recorded directly from k to i to l and merges point i；
Step 4.4, each the mergings point i of traversal, put from merging and traverse backward forward again, if i point nth section a backward
Subtract 180 degree to the direction of b, and forward the difference of the angular separation of nth section x to y be less than threshold value C, and this two sections it
Between be connection, then the section between this two sections is all deleted, individual is directly from a to y；
Step 4.5 after deleting redundancy section, rearranges trip route of the individual between O-D point, completes individual O-
The trajectory extraction of the space road traffic net of D trip.
In this example, the O-D trip route rearranged after redundancy is deleted are as follows:
L12→L13→L11→L14→L6→L8→L11→L18→L17→L19→L21→L20→L26→L48→
L54→L42→L34→L35→L36→L37→L44→L45→L47→L43→L41→L40→L72→L43→L12→
L14→L02→L10
The purpose of the present invention is extract wherein using the communication data between individual hand-held terminal device and fixed sensor
Time and space information, construct individual trip space-time data collection；Using the method for space interpolation and cluster from individual trip data
It concentrates the long-time extracted it spatially to stop ground, the O-D point that individual is gone on a journey in time series is divided with this；For a
The O-D point of body trip, using the method for spatial analysis and calculating, on the basis for calculating shortest path using dijkstra's algorithm
On, the direction in space complexity profile for constructing movement routine passes through space using the traveling time between communication node as constraint condition
The most probable path that algorithm of planning strategies for building solving equations individual moves between communication node；Most may be used between obtaining communication node
On the basis of several paths, redundancy processing and arrangement are carried out to it, the final most probable path for obtaining individual between O-D.The present invention
It, can low cost, automation, easily using having the lasting encryption position information of magnanimity anonymity mobile terminal in communication network
Obtain a large amount of individual trip Time-space serial data within the scope of specified time, on this basis to the O-D point of individual space trip into
Row judgement and identification excavate the motion track of individual using spatial operation and analytical technology, to quickly and efficiently obtain
The individual moving process and path online in road traffic are obtained, to provide data basis for timesharing highway loading situation statistics.
Claims (4)
1. a kind of method that individual trip path locus extracts under big data environment, which comprises the following steps:
Step 1, the anonymity obtained within the scope of certain time from sensor operator encrypt mobile terminal sensing data, are every
Null record when a user's building is gone on a journey by the preliminary individual that individual and fixed sensor communications records are constituted, by fixed sensor
Geographical attribute assigns each communication node in preliminary individual trip space-time trajectory, constructs individual trip space-time data collection with this；
Step 2 arranges individual trip space-time data collection in chronological order, is with the communications records between individual and fixed sensor
Node constructs individual trip Time-space serial, identifies the trip O-D point in individual trip Time-space serial, by individual space-time sequence of going on a journey
Column are cut according to O-D point, are divided into several sections O-D, and every section is numbered, and constitute the individual trip section O-D data set；
Step 3, according to the individual trip section O-D data set, calculate individual distance between node, flower two-by-two in trip section
Time-consuming and average speed, according to the speed between node two-by-two in individual trip section, by constructing network model, with practical road
The road network of communication lines is geographical substrate, calculates individual possible individual trip route between the two nodes, comprising the following steps:
Step 3.1, the road traffic net for arranging individual place city, by every roads classification in road traffic net, according to existing
There are data to obtain average movement speed of the every kind of trip mode on every road in each period；
All communication nodes in step 3.2, the section O-D data set that individual is gone on a journey in individual every section O-D are according to its sky
Between position project in road traffic net, search the road traffic net junction node nearest apart from each communication node, be defined as R
Point, using R point as the S-T point between communication node two-by-two, the shortest distance of calculating communication node to respective S-T point；
Step 3.3 extracts the shortest distance and its path between communication node two-by-two, calculates the time that shortest path is spent；
Step 3.4 is cut apart with a knife or scissors the shortest path between communication node two-by-two by section, calculates the direction in space complexity of shortest path
SDF, the direction in space complexity SDF, which are used, asks weighting standard difference to obtain the moving direction of pavement branch sections；
If the traveling time of step 3.5, individual between communication node two-by-two is less than or equal to the time that shortest path is spent, most short
Path is practical mobile section of the individual between communication node two-by-two；Otherwise, spatial operation model is constructed, using solving equations
Method using direction in space complexity SDF as objective function, solve individual in space using traveling time as constraint condition
Motion track, practical mobile section of the motion track as individual between communication node two-by-two；
Step 3.6 will solve obtained practical mobile section both ends plus communication node to the shortest distance of S-T point, constitute
Most probable individual trip route between communication node two-by-two；
Step 4 carries out arrangement and Space integration to the most probable individual trip route that all communication nodes two-by-two are calculated, most
Specific individual trip track is obtained eventually.
2. the method that individual trip path locus extracts under a kind of big data environment as described in claim 1, which is characterized in that
In the step 3.4, if individual moving direction in k-th of section between i-th of communication node and j-th of communication node is
And having N section, i.e. k=1 between i-th of communication node and j-th of communication node, 2 ..., N then calculates individual at this first
The average value of all section moving directions between i-th of communication node and j-th of communication nodeWithIt is 0 degree, it will
The direction that individual moves on N section is adjusted in [- 180,180] section, then the moving direction in k-th of section is adjusted toThen between i-th of communication node and j-th of communication node between direction in space complexity may be expressed as:
In formula,Indicate the length in k-th of section.
3. the method that individual trip path locus extracts under a kind of big data environment as claimed in claim 2, which is characterized in that
Assuming that there is L side in road traffic net, there is M junction node, starting point is node B, and terminal is node D, then in the step 3
Equation group indicates are as follows:
s.t.
In formula,Indicate the SDF value of shortest path；
SDF is the SDF value of solution path；
lm,nIt is (0-1) Boolean variable, indicates that the section of m-th of junction node to n-th of junction node is used in and ask
In solution path, if lm,n=1 indicates that the section of m-th of junction node to n-th of junction node be used to solve obtained path
In, otherwise lm,n=0；
INmIt indicates in solving obtained path, number of the individual from m-th of junction node；OUTmExpression is obtained in solution
Path in, individual reach m-th of junction node number；According to theorem on flows in network, if m-th of junction node is rising for individual
Point, then INm-OUTm=-1, if m-th of junction node is the terminal of individual, INm-OUTm=1, remaining intermediate node INm-
OUTm=0；
TIMES,TIndicate the time difference between communication node；
vm,n,t,pIt indicates in time range t, pth kind trip mode is in m-th of junction node to the section of n-th of junction node
Average movement speed；
Indicate using pth kind trip mode in time range t, along solve obtained path from B point to
D point the time it takes, rm,nIndicate m-th of junction node to n-th of junction node road section length.
4. the method that individual trip path locus extracts under a kind of big data environment as described in claim 1, which is characterized in that
The step 4 includes:
Step 4.1 pieces together the most probable path between communication node two-by-two, constitutes the preliminary complete path O-D；
Step 4.2, in addition to the O point and D point, remove in the path O-D from communication node to away from nearest traffic intersection away from
From it is online that the path O-D is mapped completely to road traffic；
Step 4.3 traverses forward backward simultaneously from each R point, if there are duplicate paths near R point, deletes repetition
Section, until there is no continuous repetition section, i.e., individual reaches R point by section k to i to j, then by section j
R point is left to i to l, then deletes section i to j and j to i, individual is recorded directly from k to i to l and merges point i；
Step 4.4, each merging point i of traversal traverse forward backward again from point is merged, if merging point i nth section a backward
Subtract 180 degree to the direction of b, and forward the difference of the angular separation of nth section x to y be less than threshold value C, and this two sections it
Between be connection, then the section between this two sections is all deleted, individual is directly from a to y；
Step 4.5 after deleting redundancy section, rearranges trip route of the individual between O-D point, completes individual O-D and goes out
The trajectory extraction of capable space road traffic net.
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